Judul karya ilmiah (artikel) : Vulnerability Assessment

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LEMBAR

HASIL PENILAIAN SEJAWAT SEBIDANG ATAU PEER REVIEW KARYA ILMIAH : JURNAL ILMIAH

Judul karya ilmiah (artikel) : Vulnerability Assessment: A Comparison of Three Different City Sizes in the Coastal Area of Central Java, Indonesia

Jumlah Penulis : 5 penulis

Status Pengusul : Wiwandari Handayani, Iwan Rudiarto, Jawoto Sih Setyono, Uchendu Eugene Chigbu, Annisa Mu'awanah Sukmawati

Identitas Jurnal Ilmiah : a. Nama Jurnal : Advances in Climate Change Research b. Nomor ISSN : 1674-9278

c. Vol.,no.,bulan,tahun : Vol.8 Isuue 4, Desember 2017 d. Penerbit : Science Press - Elsevier e. DOI artikel (jika ada) : 10.1016/j.accre.2017.11.002 f. Alamat web jurnal : https://www.sciencedirect.com/

science/article/pii/S1674927

817300345?via%3Dihub

g.Terindeks di SJR Q1 1,009 (2019) dan SNIP 1,311 (2019)

Kategori Publikasi Jurnal Ilmiah : Jurnal Ilmiah Internasional /internasional bereputasi (beri pada kategori yang tepat) Jurnal Ilmiah Nasional Terakreditasi

Jurnal Ilmiah Nasional /Nasional di DOAJ,CABI, COPERNICUS

Hasil Penilaian Peer Review :

Komponen Yang Dinilai

Nilai Maksimal Jurnal Ilmiah

Nilai Akhir Yang Diperoleh Internasional/

internasional bereputasi

Nasional Terakreditasi

Nasional

a. Kelengkapan unsur isi artikel (10%) 4 4,0

b. Ruang lingkup dan kedalaman pembahasan (30%)

12 11,0

c. Kecukupan dan kemutahiran

data/informasi dan metodologi (30%)

12 11,0

d. Kelengkapan unsur dan kualitas terbitan/jurnal (30%)

12 10,0

Total = (100%) 40 36,0

Nilai = (40% x 36 : 4) 3,6

Catatan Penilaian artikel oleh Reviewer :

a. Penulisan isi artikel lengkap dan sudah mengacu kepada petunjuk penulisan artikel (author guidelines) yang disediakan oleh jurnal dalam lamannya yang terdiri dari; title, authors and affiliations, abstract-keywords, introduction, study area, data and method, results, discussion and implications, conclusion, acknowledgement, dan references. Penjelasan dan pembahasan dari setiap komponen penulisan merupakan penjabaran dan penilaian kerentanan yang tertera dalam judul artikel.

b. Pembahasan cukup mendalam berhubungan dengan penilaian tingkat kerenatanan dari 3 katagori kota (besar, menengah, dan kecil) yang ada di pesisir utara Jawa Tengah; Semarang, Tegal , dan Lasem dari aspek fisik, ekonomi, demografi, social, dan infrastruktur dan fasilitas. Artikel jurnal sesuai dengan bidang penulis terutama dalam konteks perencanaan dan pengembangan wilayah

40

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pesisir yang dikaitkan dengan climate disaster seperti bajir dan rob. Pembahasan artikel didukung oleh 10 sumber pustaka (22%) yang merupakan artikel jurnal internasional.

c. Terdapat total 46 sumber pustaka yang dipakai dan hamper semua sumber merupakan artikel jurnal internasional dimana 80% (37) diantaranya merupakan artikel terbitan 10 tahun terakhir. Data diambil dan dibahas secara komprehensif untuk 3 kotaynag dijadikan sebagai wilayah studi dengan menggunakan metode Exposure and sensitivity index (ESI) dan Adaptive Capacity Index (ACI) yang memiliki kebaruan.

d. Jurnal terindeks Scopus dengan SJR = 1,09 tergolong Q1 yang diterbitkan oleh Science Press berkolaborasi dengan Elsevier. Jurnal berbayar untuk open access dan tersedia online melalui tautan DOI dan juga dilengkapi dengan ISSN dengan editorial board yang beragam.

Semarang, 14-01-2020 Reviewer 1,

Prof. Dr.rer.nat. Imam Buchori, ST NIP. 197011231995121001 Departemen PWK, FT. Undip

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Hasil Penilaian Peer Review :

Komponen Yang Dinilai

Nilai Maksimal Jurnal Ilmiah

Nilai Akhir Yang Diperoleh Internasional/

internasional bereputasi

Nasional Terakreditasi

Nasional

a. Kelengkapan unsur isi artikel (10%) 4 4,0

b. Ruang lingkup dan kedalaman pembahasan (30%)

12 10,0

c. Kecukupan dan kemutahiran

data/informasi dan metodologi (30%)

12 10,0

d. Kelengkapan unsur dan kualitas terbitan/jurnal (30%)

12 10,0

Total = (100%) 40 34,0

Nilai = (40% x 34 : 4) 3,4

Catatan Penilaian artikel oleh Reviewer :

a. Isi artikel sesuai dengan template penulisan jurnal yang tersedia dalam laman jurnal. Penulisan dan pembahasan setiap komponen tulisan mereprsentasikan judul yang diangkat yang berhubungan dengan penilaian kerentanan untuk tiga katagori kota di Jawa Tengah.

b. Penilaian tingkat kerentanan di tiga kota di pesisir utara Jawa Tengah (Semarang, Tegal, dan Lasem) dibahas secara mendalam dari aspek demografi, ekonomi, social, fisik, dan infrastruktur dan fasilitas dengan menggunakan metode ESI dan ACI dengan melibatkan sebanyak 10 sumber pustaka dari jurnal internasional. Artikel jurnal sesuai dengan bidang ilmu penulis terutama berhubungan dengan perencanaan di wilayah pesisir yang terdampak banjir dan rob.

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c. Artikel ini didukung oleh total 46 literatur dimana 80% dianataranya merupakan artikel jurnal internasional terbitan 10 tahun terakhir. Artikel didukung oleh data dan metode kebaruan yang cukup dengan membandingkan tingkat kerentanan di tiga kota yang dinilai dimana metode penilaian kerentanan yang digunakan diadopsi dan dikembangkan dari berbagai sumber sesuai konteks wilayah studi.

d. Jurnal internasional bereputasi tinggi terbitan Science Press berkolaborasi dengan Elsevier dan terindeks Scopus dengan SJR 1,009 termasuk dalam Q1. Jurnal berbayar untuk open access dengan tautan DOI dan tersedia online dengan editorial board beragam dari berbagai negara.

Semarang, 07-02-2020 Reviewer 2,

Prof. Dr. Ir. Nany Yuliastuti, MSP NIP. 195407171982032001 Departemen PWK, FT. Undip

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LEMBAR

Hasil Penilaian Peer Review : Komponen Yang Dinilai

Nilai Reviewer

Reviewer I Reviewer II Nilai Rata- rata

a.Kelengkapan unsur isi artikel (10%) 4,0 4,0 4,0

b.Ruang lingkup dan kedalaman pembahasan (30%)

11,0 10,0 10,5

c.Kecukupan dan kemutahiran data/informasi dan metodologi (30%)

11,0 10,0 10,5

d.Kelengkapan unsur dan kualitas terbitan/jurnal (30%)

10,0 10,0 10,0

Total = (100%) 36,0 34,0 35,0

Nilai = (40% x 35 : 4) 3,5

Semarang, 09-03-2020

Reviewer 1, Reviewer 2,

Prof. Dr.rer.nat. Imam Buchori, ST Prof. Dr. Ir. Nany Yuliastuti, MSP

NIP. 197011231995121001 NIP. 195407171982032001

Departemen PWK FT.Undip Departemen PWK FT.Undip

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English | 中文

Advances in Climate Change Research

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Advances in Climate Change Research Editorial Board

Editor-in-Chief

QIN Da-He

Associate Editor-in-Chief

Deliang CHEN

DING Yi-Hui

Feifei JIN

LI Jian-Ping

LIN Er-Da

LUO Yong

PAN Jia-Hua

QI Ye

SHEN Yong-Ping

Shuaihua CHENG

SONG Lian-Chun

China Meteorological Administration

Department of Earth Sciences, University of Gothenburg

National Climate Center, China Meteorological Administration

University of Hawaii

Ocean University of China

Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences

Center for Earth System Science, Tsinghua University

Research Center for Sustainable Development, Chinese Academy of Social Sciences

Institute for Public Policy, Hong Kong University of Science and Technology

Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences

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Xiaoming WANG

Xuebin ZHANG

YU Ru-Cong

Zbyszek KUNDZEWICZ

ZHANG Xiao-Ye

ZHANG Xi-Liang

Zhifu MI

Editorial Members

Adi NUGRAHA

Annette RINKE

Arun SHRESTHA

Atsumu OHUMURA

CAO Long

CHAO Qing-Chen

CHEN Wen-Ying

CHEN Xian-Yao

Climate Data Analysis Section, Environment Canada

China Meteorological Administration

Institute for Agricultural and Forest Environment, Polish Academy of Sciences

Chinese Academy of Meteorological Sciences

School of Environment, Tsinghua University

The Bartlett School of Construction and Project Management, University College London

Paciﬁ c Northwest National Laboratory

Alfred Wegener Institute for Polar and Marine Research (AWI)

International Centre for Integrated Mountain Development, Nepal

Institute for Atmospheric and Climate Science, Swiss Federal Institute of Technology (ETH)

Zhejiang University

Institute of Nuclear and New Energy Technology, Tsinghua University

Key Laboratory of Physical Oceanography, Ocean University of China

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Chong-Yu XU

Claude BOUTRON

CUI Peng

Cun-Rui HUANG

DAI Jun-Hu

David Neil BIRD

Dirk MESSNER

Driss ENNAANAY

DUAN Mao-Sheng

Emilio BASTIDAS-ARTEAGA

GAO Qing-Xian

Hans VON STORCH

Hassan VIRJI

Helene CACHIER

HUANG Yao

Imme SCHOLZ

Department of Geosciences, University of Oslo

University Joseph Fourier of Grenoble, France

Chengdu Institute of Mountain Hazards and Environment, Chinese Academy of Sciences

School of Public Health, Sun Yat-Sen University

Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences

JOANNEUM RESEARCH Forschungsgesellschaft mbH LIFE – Centre for Climate, Energy and Society

German Development Institute; German Advisory Council on Global Change

Stanford University

Tsinghua University

Research Institute in Civil and Mechanical Engineering, University of Nantes

Chinese Research Academy of Environmental Sciences

Helmhltz Zentrum Geesthacht - Centre for Materials and Coastal Research, Germany

International START (System for Analysis, Research and Training) Secretariat

Sciences Laboratory of Climate and Environment (LSCE) of the CEA

Institute of Botany, Chinese Academy of Sciences

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JIANG Ke-Jun

JIANG Zhi-Hong

JIN Hui-Jun

Jun LI

KANG Shi-Chang

Klaus FRAEDRIC

LIN Jin-Tai

Marco GEMMER

Mohan MUNASINGHE

Mukul SANWAL

MU Mu

Ned HELME

R. Cesar IZAURRALDE

Richard ARIMOTO

German Development Institute

Institut Pierre Simon Laplace/Laboratoire des Sciences du Climat et de l’Environnement, France

Energy Research Institute, China

Nanjing University of Information Science and Technology, China

Curtin University of Technology

Meteorological Institute, KlimaCampus, University of Hamburg; Nanjing University of Information Science and Technology, China

Peking University

Munasinghe Institute for Development (MIND); Sustainable Development, University of Manchester

Advisory Committee on the National Mission on Climate Change and the Committee on the National Mission on Himalayan Ecosystems, Ministry of Science and Technology, India

Fudan University

Center for Clean Air Policy, USA

Joint Global Change Research Institute; Department of Geography, University of Maryland

Carlsbad Environmental Monitoring & Research Center, New Mexico State University

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Slobodan P. Simonovic

Sungmin HONG

SUN Jun

TENG Fei

Thomas STOCKER

Tian ZHOU

Tiejun WANG

Vilas NITIVATTANANON

WANG Yi

WU Bing-Yi

XIA Jun

XIAO Cun-De

Xiaolan L. WANG

Xin WANG

Xiuhua ZHU

School of Earth and Atmospheric Sciences, Georgia Institute of Technology

Institute for Catastrophic Loss Reduction, The University of Western Ontario

Department of Ocean Sciences, College of Natural Science, Inha University

Tianjin University of Science and Technology

Tsinghua University

Climate and Environmental Physics, Physics Institute, University of Bern, Switzerland

Paciﬁ c Northwest National Laboratory

Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente

School of Environment, Resources and Development, Asian Institute of Technology (AIT)

Institute of Policy and Management, Chinese Academy of Sciences

Fudan University

Wuhan University, China

Beijing Normal University

Climate Research Division, Atmospheric Science and Technology Directorate, Science and Technology Branch, Environment Canada

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Including special topic on U.S. withdraw from the Paris Agreement and its impacts

Edited by CHAO Qing-Chen Volume 8, Issue 4,

Pages 213-296 (December 2017) Download full issue

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Special topic on U.S. withdraw from the Paris Agreement and its impacts

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The withdrawal of the U.S. from the Paris Agreement and its impact on global climate change governance

Yong-Xiang Zhang, Qing-Chen Chao, Qiu-Hong Zheng, Lei Huang Pages 213-219

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U.S. withdrawal from the Paris Agreement: Reasons, impacts, and China's response Hai-Bin Zhang, Han-Cheng Dai, Hua-Xia Lai, Wen-Tao Wang

Pages 220-225

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The impacts of U.S. withdrawal from the Paris Agreement on the carbon emission space and mitigation cost of China, EU, and Japan under the constraints of the global carbon emission space

Han-Cheng Dai, Hai-Bin Zhang, Wen-Tao Wang Pages 226-234

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Changes in climate system

Responses and changes in the permafrost and snow water equivalent in the Northern Hemisphere under a scenario of 1.5 °C warming

Ying Kong, Cheng-Hai Wang Pages 235-244

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Comparison of climate projections between driving CSIRO-Mk3.6.0 and downscaling simulation of RegCM4.4 over China

Dong-Feng Zhang, Zhen-Yu Han, Ying Shi Pages 245-255

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Projections of future rainfall for the upper Ping River Basin using regression-based downscaling

Sirikanya Saengsawang, Phaotep Pankhao, Chanphit Kaprom, Nutchanart Sriwongsitanon Pages 256-267

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Review article Open access

Inﬂuence of climate change and human activity on water resources in arid region of Northwest China: An overview

Yu-Jie Wang, Da-He Qin Pages 268-278

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Review article Open access

Changes in classiﬁed precipitation in the urban, suburban, and mountain areas of Beijing

Yu-Feng Yuan, Pan-Mao Zhai, Jian Li, Yang Chen Pages 279-285

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Adaption to climate change

Vulnerability assessment: A comparison of three diﬀerent city sizes in the coastal area of Central Java, Indonesia

Wiwandari Handayani, Iwan Rudiarto, Jawoto Sih Setyono, Uchendu Eugene Chigbu, Annisa Mu'awanah Sukmawati

Pages 286-296

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ISSN: 1674-9278

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The withdrawal of the U.S. from the Paris Agreement and its impact on global climate change governance

ZHANG Yong-Xiang

^a

, CHAO Qing-Chen

^a,

* , ZHENG Qiu-Hong

^b

, HUANG Lei

^a

aNational Climate Center, China Meteorological Administration, Beijing 100081, China

bChina Meteorological Administration Training Center, Beijing 100081, China

Received 4 July 2017; accepted 9 August 2017 Available online 31 August 2017

Abstract

The global community has prepared for the withdrawal of the U.S. from the Paris Agreement since Donald Trump was elected as the president of the U.S. However, Trump's formal declaration of withdrawal still caused worldwide reaction. Trump will use the withdrawal to build his political reputation and to renegotiate the Paris Agreement despite its negative effects on the political credibility, international relationships, and potential long-term economic growth of the U.S. In general, the withdrawal of the U.S. from the Paris Agreement will not change the development of low-carbon technologies and the transformation trend of the global climate governance regime. However, the long-term goals and international cooperation on climate change will be affected by budget cuts in American climate change research and the cancelation of donations from the multilateral environmental fund of the U.S. If the Paris Agreement is renegotiated, the common but differentiated principle of responsibility of the United Nations Framework Convention on Climate Change will be challenged again. Nevertheless, climate change governance remains a main theme of future sustainable development. Instead of national governments, local governments and non-governmental organizations will develop strategies for technical innovation and emphasize pragmatic cooperation, thus expanding their roles in climate change governance. The capacity building on climate change research and public awareness should be enhanced as a long-term objective of global climate change governance.

Keywords:U.S. withdraw Paris Agreement; Global climate change governance; Impact

1. Introduction

Parties of the United Nation Framework Convention on Climate Change (UNFCCC) passed the Paris Agreement in its COP21 in December, 2015. As one of the most important outcomes of international multilateral progress, the Paris Agreement showed the willingness of member countries to cooperate and clearly signaled the need for the low-carbon transformation of the international society. Global cooperation on the response to climate change thus entered a new era (Zheng et al., 2016; UNEP and Bloomberg, 2017). Driven by

the strong political support, the Paris Agreement came into force shortly within a year in November, 2016. Negotiations under the framework of UNFCCC focused on the details of the Paris Agreement. However, the results of the U.S. presidential election presented potential threats to the implementation of the Paris Agreement. The new U.S. President, Donald Trump, claimed that global warming is a hoax concocted by China to weaken the competitive industrial power of the U.S. He then announced on June 1, 2017 that he had decided to pull the U.S.

out of the non-binding Paris Agreement. Claiming that the Paris Agreement restricts the U.S. while empowering other countries, Trump said the U.S. would begin negotiations to re- enter the agreement and make it“fair”to the U.S.

The withdrawal of the U.S. from the Paris Agreement aroused great response both in and outside the country. Former U.S.

President Obama pointed out that Trump's decision has made the

*Corresponding author.

E-mail address:[email protected](CHAO Q.-C.).

Peer review under responsibility of National Climate Center (China Meteorological Administration).

Available online atwww.sciencedirect.com

ScienceDirect

Advances in Climate Change Research 8 (2017) 213e219

www.keaipublishing.com/en/journals/accr/

http://dx.doi.org/10.1016/j.accre.2017.08.005

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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Projections of future rainfall for the upper Ping River Basin using regression-based downscaling

Sirikanya SAENGSAWANG, Phaotep PANKHAO, Chanphit KAPROM, Nutchanart SRIWONGSITANON *

Department of Water Resources Engineering, Faculty of Engineering, Kasetsart University, Bangkok, 10900, Thailand Received 2 February 2017; revised 9 June 2017; accepted 15 November 2017

Available online 21 November 2017

Abstract

The objective of this study was to use regression modelling, a form of statistical downscaling technique, to predict the daily rainfall occurrence and rainfall amounts for a small river basin, the upper Ping River Basin (UPRB) in northern Thailand. Daily historic (1960e2005) rainfall and a number of daily reanalysis variables (NCEP/NCAR) were used to create regression models that estimate the probabilities of rainfall occurrence (wet days) and amounts (rainfall depth) at each of 29 rain gauge stations located in and around the UPRB. The regression models were calibrated using historic (1960e1989) data and validated using historic (1990e2005) data. Regression models were later applied to historic (1960e2005) GCM outputs (MPI-ESM-LR model) which were adjusted to correspond to the selected reanalysis variables using the Nested Bias Correction (NBC) technique. Rainfall occurrence and amounts were predicted for the periods 2006e2050 and 2051e2100 for RCP2.6, RCP4.5, RCP8.5 scenarios. Results show that the effects of climate change vary considerably across the catchment, with significantly declines in both the number of wet days and rainfall depth in the wet- and especially the dry-season in the middle of the catchment but obviously increase slightly towards the northern part of the catchment. Since the stepwise regression was used to select the atmospheric variables to form the regression models for simulating rainfall occurrence and amount, different stations have their own predictors and can influence future rainfall to vary significantly between 29 rain gauge stations. If the top three predictors were selected to form the regression models for simulating rainfall occurrence and amount for all stations, the future rainfall characteristics possibly change and can be used to compare with those of presented in this study. It will show either atmospheric predictors or climate change scenarios would have more effect on future rainfall characteristics.

Keywords:Statistical downscaling; Nested bias correction; MPI-ESM-LR model; Representation concentration pathways (RCPs); Ping River Basin

1. Introduction

An assessment of climate change impacts on hydrological studies requires outputs of experiments from General Circu- lation Models (GCMs). However, the GCMs are constrained by their coarse spatial resolution to be used for resolving local scale hydrological processes (Wilby and Wigley, 1997; Wilby et al., 1999; Timbal et al., 2009). Downscaling techniques

have therefore emerged to relate the regional scale atmospheric variables to the local scale surface variables. Down- scaling approaches can be separated into two categories;

dynamical and statistical techniques. Strengths and weak- nesses of these two downscaling categories are clearly presented by Wilby et al. (2002). In dynamic downscaling referred to as the Regional Climate Models (RCMs), the time- varying atmospheric conditions supplied by GCMs are used to drive a regional, numerical model in higher spatial resolution (tens of kilometres) to simulate local conditions in greater details. On the other hand, a statistical downscaling establishes a statistical relationship from observations between large scale variables and a single local variable and then subsequently

*Corresponding author.

E-mail address:[email protected](SRIWONGSITANON N.).

Peer review under responsibility of National Climate Center (China Meteorological Administration).

Available online atwww.sciencedirect.com

ScienceDirect

Advances in Climate Change Research 8 (2017) 256e267

www.keaipublishing.com/en/journals/accr/

https://doi.org/10.1016/j.accre.2017.11.001

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).